Wireless communication devices and wireless networks have proliferated in recent years. This has resulted in region having different electromagnetic spectrum profiles. For example, in some regions geographic as well as population conditions have resulted in relatively crowded local frequency spectra. Although both regulatory agencies (such as the FCC in the United States) and manufacturers have attempted to regulate and minimize such crowding, it has proven difficult to optimize and prevent interference across commercially relevant portions of the electromagnetic spectrum. In particular, electromagnetic interference, from both natural and man-made sources, is difficult to predict and to avoid. Unfortunately, electromagnetic interference causes significant problems for wireless devices and networks. Electromagnetic interference can arise from other communication devices even if those other devices use a different carrier frequency. For example, a cordless telephone using a first carrier frequency could generate electromagnetic interference that makes it difficult for a communication device using a second carrier frequency to maintain connection to a local area network (LAN). Electromagnetic interference might also arise from electronic devices other than communication devices (e.g., microwave ovens, etc.).
Determining the source of interference and/or preventing or avoiding it has proven difficult. One reason for the challenge is that the interference may be sporadic. Another reason is that device could be mobile, as could sources of interference.
Since electromagnetic interference can be highly local, and interference in the electromagnetic spectrum seen by some devices may not be seen by other devices even in the same network, it would be helpful to be able to monitor local interference at a wireless radio device, including at both ends of link in a network, such as at an access point (AP) and at an end device (e.g., a customer provided equipment, or CPE). In addition, since electromagnetic “traffic” and interference may vary greatly over time, it would be helpful to monitor continuously.
As an example, a particular wireless communication device that operates in compliance with an 802.11 protocol might be experiencing periodic problems associated with electromagnetic interference. An analysis of the local frequency spectrum content of the operating band may be used to optimize performance of the local device as well an entire network. Spectrum content can be determined by a spectrum analyzer, which can monitor frequency domain.
Thus, there is a need for devices and systems, and particularly wireless radio devices and systems, that provide both local monitoring of the frequency spectrum of a broadly-defined operating band while concurrently (and in some cases independently) receiving and transmitting wireless radio frequency signals.
In superheterodyne receivers there are known vulnerabilities or spurious responses which may interfere with signal transmission. There are many types spurious interference, including, for example, the half-intermediate frequency (or “half-IF”) response. In such receiver circuits, mixers typically translate a high input radio frequency (RF) to a lower intermediate frequency (IF). This process is known as down-conversion utilizing the difference term between a mixer's RF input and a local oscillator input (LO) for low-side injection (LO frequency <RF frequency) or the difference term between the mixer's LO and RF for high-side injection. This down conversion process can be described by the following equation: fIF=±fRF±fLO, where fIF is the intermediate frequency at the mixer's output port, fRF is any RF signal applied to the mixer's RF input port, and fLO is the local oscillator signal applied to the mixer's LO input port.
Ideally, the mixer output signal amplitude and phase are proportional to the input signal's amplitude and phase and independent of the LO signal characteristics. Under this assumption, the amplitude response of the mixer is linear for the RF input and is independent of the LO input. However, mixer nonlinearities may produce undesired mixing products called spurious responses, which are caused by undesired signals reaching the mixer's RF input port and producing a response at the IF frequency. The signals reaching the RF input port do not necessarily have to fall into the desired RF band to be troublesome. Many of these signals are sufficiently high in power level that the RF filters preceding the mixer don't provide enough selectivity (e.g., rejection) to keep them from causing additional spurious responses. When they interfere with the desired IF frequency, the mixing mechanism can be described by: fIF=±m*fRF±n*fLO. Note that m and n are integer harmonics of both the RF and LO frequencies that mix to create numerous combinations of spurious products. The amplitude of these spurious components typically decreases as the value of m or n increases.
Knowing the desired RF frequency range, frequency planning is used to carefully select the IF and resulting LO frequency selections to avoid spurious mixing products whenever possible. Filters are typically used to reject out-of-band RF signals that might cause in-band IF responses. IF filter selectivity following the mixer is specified to pass only the desired frequencies thereby filtering the spurious response signals ahead of the final detector. However, spurious responses that appear within the IF band will not be attenuated by the IF filter.
The half-IF spurious response is a particularly troublesome 2nd-order spurious response, which may be defined for the mixer indices of (m=2, n=−2) for low-side injection and (m=−2, n=2) for high-side injection. For low-side injection, the input frequency that creates the half-IF spurious response is located below the desired RF frequency by an amount fIF/2 from the desired RF input frequency.
The half-IF frequency represents a frequency where interference will be converted to the IF frequency just like the desired receiver signal, but at a reduced efficiency. Unlike the image which is relatively easy to filter out due to the large frequency difference from the desired signal, or signals that may cause blocking (which require very large signals), the half-IF response can significantly impact achievable performance. Other spurious responses may be found at other frequencies within the transmission bandwidth. In order to make a broadband wireless radio device more selective, described herein are superheterodyne receivers that may mitigate the vulnerabilities/side-effects described above. In particular, described herein are devices and mechanisms that alter the intermediate frequency based on the detected or predicted distractors (e.g., spurious responses) at predetermined frequencies, including in particular the half-IF spurious response. This mechanism of dynamically changing the frequency plan in response to actual interference to avoid predictable spurious is applicable to other spurious vulnerabilities as well as the half-IF frequency (e.g., adjacent channel interference, 2×2 spurious responses, and other interferers).